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New and emerging technology for adult social care – the example of home sensors with artificial intelligence (AI) technology · Findings: Decision-making to adopt AI in social care

Findings: Decision-making to adopt AI in social care

CC BY 4.0 · National Institute for Health and Care Research · approximately 7 min read

Box 9 provides a summary of Chapter 5 of this report.

Summary of key points

  • There appeared to be no systematic decision-making process; in its absence, a number of contextual factors influenced procurement decisions, including perceived pressure from central bodies to invest in technology-enabled care solutions and a more general belief in the capabilities of technology.
  • The identification and exploration of options and alternatives often appeared ad hoc in nature and frequently relied on word of mouth and/or a relatively superficial appraisal of the suitability of the technology, informed by the quality of the sales pitch and the aesthetic characteristics of the hardware.
  • There may be scope for the decision-making process to be more structured and, where broad-ranging changes are envisaged, more strategic in nature.

The social care sector is under growing pressure as financial constraints and workforce shortages are compounded by the increasing demands of an ageing population. In meeting this need, sites described the expectation from central government and national bodies that they would maximise the use of technology to help manage the mismatch between demand and resource:

Politicians having a belief that technology was the magic bullet for social care and it would save millions and, you know, make all the needy people go away, kind of thing… We were under a lot of pressure to innovate and be seen to be forward looking and, you know, all of that stuff.

Perhaps unsurprisingly with approaches that are ‘new and emerging’, sites did not seem to have a systematic process for identifying and appraising the range of technological options available. As the technology provider observed, the typical approach is often to purchase the technology then find a use for it:

I would say probably the most common approach is that we’re aware that technology is moving on and we feel we should adopt some of it, but we don’t know what and we don’t know why, but we just want to see what it is and how it might help.

In practice, sites tended to rely on trusted intermediaries such as a local provider or their peers in other organisations, as well as on ‘showcase’ events where a number of technology providers gathered to present their products and provide practical demonstrations to representatives from across health and social care. Arguably the most structured process was discovered at site 2, where a group of ‘Tech-Champions’ was created to explore technology-based care solutions. While this seemed a helpful way of ensuring two-way dialogue between different stakeholders, with scope to test new ways of working in a very flexible manner, the approach seemed to be primarily a pragmatic and opportunistic one, rather than a systematic attempt to identify and weigh all the different options. More commonly, sites recognised that they often lacked the necessary technical and IT expertise to ask the right questions of technology providers during the procurement process:

What we’re experts in is providing social care to people. So having somebody who understands these things and can kind of be a sense-check and go ‘sounds good but can it actually…? Where’s that evidence base for this? Has that company tried this out somewhere? Do they have really good data to back up their claims?’

From another perspective, the technology provider felt that a lack of technical expertise among the sector led to unrealistic assumptions being made about what the technology might accomplish:

They have completely unrealistic expectations of what it can do, like they imagine that it will phone an ambulance for them or, you know, stuff like that. And so they don’t have typically a really kind of realistic view of what is and is not possible in terms of technology. So we spent an awful lot of time working with them to educate them really, I guess, in terms of what the technology does and doesn’t do, what its limitations are, and I would say that they are surprised at what it can do more than they’re disappointed at what it can’t do.

The pressure to engage with technology-enabled care solutions and the lack of technical expertise were compounded by the need for the public services involved in the pilots to work closely with a commercial company, with mixed reports from our interviews as to the degree of collaboration and trust between social care organisations and IndependencePlus. Some felt the company may have been withholding information about previous experiences of other sites using IndependencePlus or otherwise may have been trying to ‘run before it could walk’ and expanding too quickly. More broadly, these suspicions surfaced as a general mistrust voiced by public sector workers of the motivation of their counterparts in private-sector, profit-driven companies:

IndependencePlus are a private company who have a product that they are trying to sell, you know, so… maybe sometimes it felt like their drivers weren’t about preventing a decline in independence but may be more about, you know, you know – trying to sell their products.

Within this broader context, three factors appeared central to the final decision to procure IndependencePlus, namely: the quality of the pitch; their ability to operate at scale; and an understanding of the potential of sensor-based remote monitoring. These are further explained in Box 10.

  • The quality of the presentation/pitch: At all three of our sites, the persuasiveness of the initial and subsequent presentations by IndependencePlus encouraged its selection ahead of other options in the field.
  • Perceived ability to operate at scale: For one large local authority, it was important that the technology had the ability to be used at scale. Other options in the marketplace seemed to be smaller and from less mature organisations lacking sufficient capacity.
  • Familiarity with sensor-based technology: Two sites recognised the potential advantages of connecting sensor-based technology to an AI system, having previously used a more limited alert-based technology involving a less sensitive set of sensors without the ability to infer specific activities or record baseline data over a period of months.

Consultation with stakeholders

Having seen or heard of new technology that might be promising, sites adopted a range of approaches to consulting with local stakeholders. A local lead at site 3 described a series of meetings and workshops that included their reablement service, their ‘care alarm service’ that monitored alerts, and a number of social care practitioners. At site 2 they adopted a different approach which involved convening a smaller core group who worked closely with the provider, effectively becoming ‘ambassadors’ for the technology and installing the system in a ‘show home’ to demonstrate its capabilities:

The [senior commissioner] gathered a small team around [them] who focused on that piece of work. And the people who worked quite closely with it at that point were very, very enthusiastic and big ambassadors for it and really wanted to try this. And we had things like a kind of demonstration ‘show home’ type of thing that we put in and we showed it to elected members and, you know, a bit of a roadshow around and tah dah! A kind of big fuss!

However, a key issue was the perceived gap between senior decision-making and front-line care delivery (which is presumably a risk in all big organisations). Despite the various workshops and demonstrations, there was little evidence of detailed and two-way consultation with front-line care staff to understand their perspectives, aspirations, anxieties and likely responses before taking the decision to proceed with a local pilot. As one senior manager described:

I think sometimes we have a danger of working in siloes so like the... team who are looking at different types of technologies might go out but they might not necessarily understand what is definitely needed on the front by a practitioner in order to benefit their assessments, and what was really appealing and really exciting and innovative from their perspective isn’t necessarily the same from my perspective.

Only one site described presenting the technology to those drawing on care and support in order to seek their upfront feedback in terms of acceptability. This could sometimes lead to significant issues further down the line – as in one site where it emerged that wheelchair users were asked to wear a device which recorded ‘steps’:

A subtle but relevant point was that the wristwatches on the IndependencePlus system presented data as ‘steps’ rather than movement and some of the users of wheelchairs here were quite affronted, understandably, that ‘this isn’t measuring steps because I’ve not taken a step in my life!’

Decision to stop using IndependencePlus

Interviewees did not provide detailed information regarding the decision to stop using IndependencePlus, although some referred to the disruption caused by the COVID-19 pandemic, and the changes that the company had implemented as a result of the pandemic (see Chapter 9 for details). However, as we discuss throughout this report, the technology had in many cases not lived up to expectations, and there were challenges around the technological capabilities and the ability to use the equipment for multiple patients. Because of these difficulties, sites may have chosen to discontinue their use of the technology regardless of the pandemic.

← Findings: Expectations of those adopting AI in social careFindings: Implementation of AI in social care →

Attribution. Jon Glasby; Ian Litchfield; Sarah Parkinson; Lucy Hocking; Denise Tanner; Bridget Roe et al. (2023). New and emerging technology for adult social care – the example of home sensors with artificial intelligence (AI) technology. National Institute for Health and Care Research. Copyright © 2023 Glasby et al. Licensed under CC BY 4.0. NCBI Bookshelf NBK593317. CC BY 4.0. Original source ↗. Text reproduced from the Bookshelf XML without changing wording; figures, images and supplements are not reproduced.

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